In the previous
post I gave you all a glimpse of business application of Artificial
Intelligence.
Red, green and blue (RGB) are the primary colours of the colour spectrum ,by varying the amount of red, green and blue light, all of the colours in the visible spectrum can be produced by the human eye.
(There is also GREY SCALE MIXING = Rods)
Every Artificial Intelligent Algorithm comes from Nature's Intelligence.
Computer
vision was one such topic that i raised!
One of the
advancement in computer vision with deep learning is called as “Convolutional neural network”.
There is a
quote in the movie –“The man who knew infinity”
There is a dialogue in the movie:
"We are merely explorers of infinity in
the pursuit of absolute perfection. We do not invent formulaes, they
already exist in the nature we are only exploring them"
Convolutional neural network is
a replica of Human Eye Model .
Convolutional neural network (CNN) is all about Image Processing and Analytics.
The agenda of CNN is to make the machines view the world as human beings.
Today we will not explore CNN rather since CNN Model is inspired by the human eye,
we will explore the various ways in which a human eye process an Image.
Universe is
made up of Electromagnetic Radiation (Energy + Wavelength + Frequency)
Frequency is
measured in cycles per second, or Hertz.
Wavelength is measured in meters.
Energy is measured in electron
volts.
The image
below shows where you might encounter each portion of the EM spectrum in
your day-to-day life.
Borrowed
from NASA - https://imagine.gsfc.nasa.gov/science/toolbox/emspectrum1.html
As seen
above, the visible spectrum of Electromagnetic spectrum is called as – “LIGHT” which we will study in detail
today.
NASA
definition of LIGHT: LIGHT is the common term for electromagnetic radiation,
usually referring to that portion visible to the human eye. However other
bands of the EM spectrum are
also often referred to as different forms of light.
The main source
of light on earth is SUN. Other
sources of light includes Lamps, fire,
power systems, electric lights. Some species
like fireflies and vampire squids generate their own light.
A light consist of spectrum of all colours.
Light is
made up of wave lengths ranging from Violet 400 nm to Dark Red 700 nm, each
wave length corresponds to a particular colour as seen below
CNN works exactly the way a Human Eye works which means - your eyes are running CNN Models every time you observe or see something?
Today we are applying this Human Eye Model to computer vision.
Let us study Human Eye Model in detail
Our understanding of light and colour began
with Isaac Newton (1642-1726)
Newton
observed that colour is not inherent in objects, the surface of the object:
1) Reflect some colours – Visible to Human Eye
2) Absorbs some colours
Thus, red is
not "in" an apple. The surface of the apple is reflecting the
wavelengths we see as red and absorbing all the rest of the wavelength.
An object
appears white when it reflects all wavelengths and black when it absorbs them
all.
Red, green and blue (RGB) are the primary colours of the colour spectrum ,by varying the amount of red, green and blue light, all of the colours in the visible spectrum can be produced by the human eye.
Human eye and how do we see light?
Do you know a human eye can perceive about 382000 different colours?
How do we do it?
Human eye is
lined with a thin layer called the retina.
Photo-receptors
are located in the retina
There are 2
types of photo receptors –Rods and Cones
If eye was a
camera, the retina would be the film.
Rods: GREY
Rods are
responsible for vision at low light levels.
We use Rods
for night vision, Rods don’t help In colour vision, in the night we see
everything in GREY SCALE
Human eyes has 100 million rod cells
Cones: RED, BLUE,
GREEN
There are 3
types of Cone: RED, BLUE, GREEN
Cones help
us visualise the detail of any image.
Variety of
colours are produced with by mixing RED, BLUE, and GREEN
Human eyes has 6 million Cones
The human
eye and brain together translate light into colour. The colour perceived by human is the sum of:
•
the
energy spectrum of the light
•
the
reflection spectrum of the object
•
the
response spectrum of the eye
382000 different
colours are perceived by human eye by some kind of colour mixing classification
system. Colour mixing Model of the Human Eye can be classified into following types.
There has been some recent innovations about which iam not writing now.
1) CIE(commission Internationale de l’Ḗclairage)
standard
Ø Cannot be replicated by a computer model
Ø each
colour = a weighted sum of three imaginary primary colours, meaning you can
simply imagine 3 colours and mix them to produce a new colour inside your eye.
This is called as ”Power of Imagination” which is something that CNN is not
capable of doing and only human eye can do.
2) RGB colour model - RED , BLUE ,GREEN.
Ø
all
colours perceived by the human eye are generated from the above three primaries
Ø
various
colours are obtained by changing the amount of each primary
Ø
additive
mixing (r,g,b), 0≤r,g,b≤1
3) CMY colour model (also, CMYK)
Ø
cyan,
magenta and yellow are complimentary colours of red,green and blue,
respectively
Ø
subtractive
mixing
Ø
For
printing and graphics art industry, CMY
is not enough; a fourth primary, K which stands for black, is added.
HSL (hue, saturation,
lightness) and HSV (hue, saturation,
value) are alternative
representations of the RGB
colour model, designed in the 1970s by computer
graphics researchers to more
closely align with the way human vision perceives colour-making attributes.
4) HSV colour model separates Image intensity from colour formation which is absent in RGB Model. Hence many Computer Vision Algorithms uses this Model for image processing and detection.(Better fit for Clinical Trial Imaging)
Ø HSV stands for Hue-Saturation-Value
Ø described by a hexcone derived from the
RGB cube
5) HSL colour model
Ø Another model similar to HSV is HSL
Ø HSL stands for Hue-Saturation-Lightness
(There is also GREY SCALE MIXING = Rods)
Every Artificial Intelligent Algorithm comes from Nature's Intelligence.
In the coming days we will explore the origin of each of the Artificial Intelligence Algorithms and how and why they are applied.
As iam not an engineer i will not be able to provide information about coding , but yes economic aspect of these will be discussed in great detail.
In my next post i will explain CNN in the form of conceptual design required for business application.
In my next post i will explain CNN in the form of conceptual design required for business application.
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